Artificial Intelligence
AI 210 - Exploring Artificial Intelligence
Description: Explores the machine learning models and algorithms that support artificial intelligence technologies through hands-on experimentation that does not demand a technical background. Students explore the fundamentals of techniques from supervised learning algorithms including decision trees, k-nearest neighbors, Naive Bayes, logistic regression, support vector machines, random forests, and neural networks, as well as unsupervised methods including clustering and dimensionality reduction, as a means to understanding the capabilities and limitations of AI. Students work with real-world datasets throughout, practicing the complete modeling pipeline from exploratory data analysis through preprocessing, training, evaluation, and interpretation, preparing for the analysis of a real-world dataset and applying AI to areas of interest. Letter grade only.
Units:
3
No sections currently offered.
Requirement Designation:
Prerequisite: AI 101